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Salary
≈ $88k – $203k per year (Estimated)
Location
In office (Dublin)
Seniority
Staff · 8+ years exp

Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Oct 19, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

Our Solutions Engineers for AI Infrastructure own complex customer issues and provide specialized support to other teams. In this role, you will be a part of a global team that provides 24x7 support to ensure customers can seamlessly deploy their AI and ML workloads on AI Infrastructure products.

When customers encounter deep technical issues, your job is to ensure we have the expertise, tools, and processes to resolve the issue. You will handle customer escalations by combining business acumen with technical skills. You will develop team members into highly skilled troubleshooting experts who can diagnose a wide variety of issues within the hardware and software boundary within minutes. You will lead operational excellence within the team with a focus on reliable execution. You will help drive business growth by recognizing and advocating for our customers challenges related to AI deployments.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Ireland: €144000 - €147000 (EUR) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Lead a team of Support Engineers who deliver technical support across our AI Infrastructure products, focusing on managing customer’s problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure.
  • Resolve high-profile escalations and issues, improve the customer experience and drive initiatives that increase their long term success.
  • Develop the vision, goals, priorities and work alongside the team to accomplish them. Ensure high-quality customer experience and ongoing technical skill development.
  • Partner with product management and engineering to translate customer needs into a better overall product. Recognize trends in customer feedback and escalate issues within Google.
  • Be available for non-standard work hours or shifts which may include weekends as needed.

Qualifications

Minimum qualifications:

  • Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  • 8 years of experience in support engineering, software development, professional services, product operations management, or other relevant areas.
  • 2 years of experience managing a technical team in a cloud computing environment or customer-facing role.
  • Experience with hardware and software support, and AI/ML data center deployments and architectural configurations.
  • Experience reading, reviewing, and writing code in one or more general purpose programming languages (e.g., C++, Java, Python, Go, etc.).

Preferred qualifications:

  • Experience working with large-scale distributed systems, and familiarity with common solutions, design patterns, or best practices.
  • Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
  • Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
  • Experience with Linux/Unix systems and expertise in debugging complex issues across the hardware/software boundary on enterprise-grade server infrastructure.
  • Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
  • Excellent troubleshooting, attention to detail, and communication skills.
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